July 09, 2017
100 deaths daily.
Impact on malaria incidence (burden)
Impact on labour force (absenteeism and productivity)
3. Impact on school age children (absenteeism and performance)
| Characteristic | Manhiça | Magude |
|---|---|---|
| Age mean | 9.38 | 9.20 |
| Age SD | 2.70 | 2.81 |
| Education mean | 2.40 | 2.51 |
| Education SD | 1.19 | 1.40 |
| Females | 2777.00 | 899.00 |
| Males | 2869.00 | 877.00 |
| N | 7671.00 | 3693.00 |
| Ses asset score mean | 6972.72 | 6770.72 |
| Ses asset score SD | 961.59 | 852.05 |
| Siblings mean | 4.48 | 4.41 |
| Siblings SD | 2.52 | 2.85 |
In diff-diff models: assumption: parallel trends (in the outcome variable) in treatment and control groups before the introduction of the intervention In order to check this crucial assumption…
The coefficients for the interaction between trimester and intervention area identify the differential trends in the outcome variable over time between the treated and control regions. Thus, as the policy is implemented in 2016, these coefficients identify any differential pre-trends in the outcome variable between treated and control regions (the crucial assumption for diff-diff models).
| Term | Key | 1 | 2 | 3 |
|---|---|---|---|---|
| After | Estimate | 0.002 | 0.003 | 0.003 |
| P | 0.128 | 0.019 | 0.019 | |
| S.E. | 0.002 | 0.001 | 0.001 | |
| After:Intervention | Estimate | 0.021 | 0.02 | 0.02 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.003 | 0.003 | 0.003 | |
| (Intercept) | Estimate | 0.867 | 0.963 | 0.964 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.002 | 0.002 | 0.002 | |
| Intervention | Estimate | 0.044 | 0.036 | 0.036 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.005 | 0.005 | 0.005 |
All regressions controlling for school. Regressions II and III also controlling for subject.
**The impact of the policy is to increase the probability of passing the exam by 2 percentage points. Given that the proportion of those passing examinations was 87.5% in the intervention area in 2015, the increase due to the intervention is (0.02/0.875*100) 2.28%.**
| Term | Key | value |
|---|---|---|
| After | Estimate | 0.006 |
| S.E. | 0.005 | |
| P | 0.253 | |
| factor(trimester)2 | Estimate | < 0.001 |
| S.E. | 0.005 | |
| P | 0.003 | |
| factor(trimester)3 | Estimate | < 0.001 |
| S.E. | 0.005 | |
| P | < 0.001 | |
| After:Intervention | Estimate | 0.052 |
| S.E. | 0.01 | |
| P | < 0.001 | |
| (Intercept) | Estimate | 0.786 |
| S.E. | 0.007 | |
| P | < 0.001 | |
| Intervention | Estimate | 0.026 |
| S.E. | 0.018 | |
| P | 0.143 |
The impact of the policy is to increase the probability of passing the exam by 5 percentage points for the case of maths. Given that the proportion of those passing examinations was 76.69% in the intervention area in 2015, the increase due to the intervention is (0.05/0.7669*100) 6.52%.
OLS regression; regression controlling for school (coeff not shown);
| Term | Key | 1 | 2 | 3 |
|---|---|---|---|---|
| After | Estimate | 0.169 | 0.175 | 0.175 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.014 | 0.014 | 0.014 | |
| After:Intervention | Estimate | 0.233 | 0.229 | 0.229 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.026 | 0.026 | 0.026 | |
| (Intercept) | Estimate | 11.822 | 12.18 | 12.167 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.015 | 0.02 | 0.022 | |
| Intervention | Estimate | 0.017 | < 0.001 | < 0.001 |
| P | 0.72 | 0.507 | 0.509 | |
| S.E. | 0.048 | 0.047 | 0.047 |
The impact of the policy is to increase the grade for all subjects by 0.23 percentage points. Given that the mean grade was 12.11 in the intervention area in 2015, the increase due to the intervention is (0.22/12.11*100) 1.9%.
| Term | Key | value |
|---|---|---|
| After | Estimate | 0.153 |
| S.E. | 0.046 | |
| P | < 0.001 | |
| factor(trimester)2 | Estimate | < 0.001 |
| S.E. | 0.047 | |
| P | < 0.001 | |
| factor(trimester)3 | Estimate | < 0.001 |
| S.E. | 0.048 | |
| P | < 0.001 | |
| After:Intervention | Estimate | 0.529 |
| S.E. | 0.088 | |
| P | < 0.001 | |
| (Intercept) | Estimate | 12.087 |
| S.E. | 0.058 | |
| P | < 0.001 | |
| Intervention | Estimate | < 0.001 |
| S.E. | 0.158 | |
| P | 0.005 |
| Term | Key | value |
|---|---|---|
| (Intercept) | Estimate | 0.965 |
| Estimate | 0.056 | |
| -1 Period | Estimate | < 0.001 |
| 1 Period | Estimate | 0.004 |
| -2 Period | Estimate | < 0.001 |
| 2 Period | Estimate | < 0.001 |
| -3 Period | Estimate | 0.002 |
| -1 Time::Intervention | Estimate | < 0.001 |
| 1 Time::Intervention | Estimate | 0.002 |
| -2 Time::Intervention | Estimate | < 0.001 |
| 2 Time::Intervention | Estimate | < 0.001 |
| -3 Time::Intervention | Estimate | < 0.001 |
| Term | Key | value |
|---|---|---|
| (Intercept) | Estimate | 0.783 |
| S.E. | 0.007 | |
| P | < 0.001 | |
| Estimate | 0.086 | |
| S.E. | 0.02 | |
| P | < 0.001 | |
| -1 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.003 | |
| 1 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.82 | |
| -2 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.02 | |
| 2 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.159 | |
| -3 Period | Estimate | 0.015 |
| S.E. | 0.009 | |
| P | 0.092 | |
| -1 Time::Intervention | Estimate | < 0.001 |
| S.E. | 0.017 | |
| P | 0.004 | |
| 1 Time::Intervention | Estimate | < 0.001 |
| S.E. | 0.016 | |
| P | 0.874 | |
| -2 Time::Intervention | Estimate | < 0.001 |
| S.E. | 0.017 | |
| P | 0.001 | |
| 2 Time::Intervention | Estimate | < 0.001 |
| S.E. | 0.016 | |
| P | 0.207 | |
| -3 Time::Intervention | Estimate | < 0.001 |
| S.E. | 0.017 | |
| P | < 0.001 |
Showing the difference between 2015 and 2016 average grades
2162 of 5162 (41.88%)
(One observation = 1 trimester-class)
(One observation = 1 trimester-class)
1737 of 4662 (37.26%)
(One observation = 1 student-day)
(One observation = 1 student-day)
860927 student-days observed (absenteeism)
222503 student-class-trimesters observed (performance)